[Bugfix] Fix HunyuanVideo-1.5 CI failures (#2066)

Signed-off-by: lishunyang <lishunyang12@163.com>

tests/e2e/online_serving/test_hunyuan_video_15_expansion.py

@@ -5,7 +5,7 @@ Tests of common diffusion feature combinations in online serving mode
 for HunyuanVideo-1.5-T2V (480p).
 
 Coverage (H100, since model cannot fit L4):
-- TeaCache + Layerwise CPU offloading (1 GPU)
+- CacheDiT + Layerwise CPU offloading (1 GPU)
 - CacheDiT + TP=2 + VAE patch parallel=2 (2 GPUs)
 """
 
@@ -34,17 +34,17 @@ def _get_diffusion_feature_cases(model: str):
     Designed for 2x H100 environment per issue #1832.
     """
     return [
-        # (1 GPU) TeaCache + Layerwise CPU offloading
+        # (1 GPU) CacheDiT + Layerwise CPU offloading
         pytest.param(
             OmniServerParams(
                 model=model,
                 server_args=[
                     "--cache-backend",
-                    "tea_cache",
+                    "cache_dit",
                     "--enable-layerwise-offload",
                 ],
             ),
-            id="single_card_teacache_layerwise",
+            id="single_card_cachedit_layerwise",
             marks=SINGLE_CARD_MARKS,
         ),
         # (2 GPUs) CacheDiT + TP=2 + VAE patch parallel=2

vllm_omni/diffusion/models/hunyuan_video/pipeline_hunyuan_video_1_5.py

@@ -68,10 +68,15 @@ def extract_glyph_texts(prompt: str) -> str | None:
 def get_hunyuan_video_15_post_process_func(od_config: OmniDiffusionConfig):
     video_processor = VideoProcessor(vae_scale_factor=16)
 
-    def post_process_func(video: torch.Tensor, output_type: str = "np"):
+    def post_process_func(video: torch.Tensor, output_type: str = "pil"):
         if output_type == "latent":
             return video
-        return video_processor.postprocess_video(video, output_type=output_type)
+        result = video_processor.postprocess_video(video, output_type=output_type)
+        # postprocess_video returns List[List[PIL.Image]] (batch x frames).
+        # Flatten to a flat list of PIL Images for the serving endpoint.
+        if isinstance(result, list) and result and isinstance(result[0], list):
+            result = result[0]
+        return result
 
     return post_process_func